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Stock trade app Robinhood raising at $5B+, up 4X in a year
By adding a cryptocurrency exchange, a web version and stock option trading, Robinhood has managed to quadruple its valuation in a year, according to a source familiar with a new round the startup is raising. Robinhood is closing in on around $350 million in Series D funding led by Russian firm DST Global, the source says. That’s just 11 months after Robinhood confirmed TechCrunch’s scoop that the zero-fee stock trading app had raised a $110 million Series C at a $1.3 billion valuation. The new raise would bring Robinhood to $526 million in funding.
Details of the Series D were first reported by The Wall Street Journal.
The astronomical value growth shows that investors see Robinhood as a core part of the mobile finance tools upon which the next generation will rely. The startup also just proved its ability to nimbly adapt to trends by building its cryptocurrency trading feature in less than two months to make sure it wouldn’t miss the next big economic shift. One million users waitlisted for access in just the five days after Robinhood Crypto was announced.
The launch completed a trio of product debuts. The mobile app finally launched a website version for tracking and trading stocks without a commission in November. In December it opened options trading, making it a more robust alternative to brokers like E*Trade and Scottrade. They often charge $7 or more per stock trade compared to zero with Robinhood, but also give away features that are reserved for Robinhood’s premium Gold subscription tier.
Robinhood won’t say how many people have signed up for its $6 to $200 per month Gold service that lets people trade on margin, with higher prices netting them more borrowing power. That and earning interest on money stored in Robinhood accounts are the startup’s primary revenue sources.
Rapid product iteration and skyrocketing value surely helped recruit Josh Elman, who Robinhood announced yesterday has joined as VP of product as he transitions to a part-time roll at Greylock Partners. He could help the company build a platform business as a backbone for other fintech apps, they way he helped Facebook build its identity platform.
In effect, Robinhood has figured out how to make stock trading freemium. Rather than charge per trade with bonus features included, Robinhood gives away the bare-bones trades and charges for everything else. That could give it a steady, scalable business model akin to Dropbox, which grew by offering small amounts of free storage and then charging for extras and enterprise accounts. From a start with free trades, Robinhood could blossom into a hub for your mobile finance life.
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Volley’s voice games for smart speakers have amassed over half a million monthly users
The rapid consumer adoption of smart speakers like Amazon Echo and Google Home has opened opportunities for developers creating voice apps, too. At least that’s true in the case of Volley, a young company building voice-controlled entertainment experiences for Amazon Alexa and Google Home. In less than a year, Volley has amassed an audience north of 500,000 monthly active users across its suite of voice apps, and has been growing that active base of users at 50 to 70 percent month-over-month.
The company was co-founded by former Harvard roommates and longtime friends, Max Child and James Wilsterman, and had originally operated as an iOS consultancy. But around a year and a half ago, Volley shifted its focus to voice instead.
“When we were running the iOS business, we were always sort of hacking around on games and some stuff on the side for fun,” explains Child. “We made a trivia game for iOS. And we made a Facebook Messenger chatbot virtual pet,” he says. The trivia game they built let users play just by swiping on push notifications — a very lightweight form of gameplay they thought was intriguing. “Voice was sort of the obvious next step,” says Child.
Not all their voice games have been successful, however. The first to launch was a game called Spelling Bee that users struggled with because of Alexa’s difficulties in identifying single letters — it would confuse a “B,” “C,” “D” and “E,” for example. But later titles have taken off.
Volley’s name-that-tune trivia game “Song Quiz” was its first breakout hit, and has grown to become the No. 1 game by reviews. The game today has a five-star rating across 8,842 reviews.
Another big hit is Volley’s “Yes Sire,” a choose-your-own-adventure style storytelling game that’s also at the top of Alexa’s charts. It also has a five-star rating, across 1,031 reviews.
The company says it has more than a dozen live titles, with the majority on the Alexa Skill Store and a few for Google Assistant/Google Home. But it only has seven or eight in what you would consider “active development.”
Unlike some indie developers who are struggling to generate revenue from their voice applications, Volley has been moderately successful thanks to Amazon’s developer rewards program — the program that doles out cash payments to top performing skills. While the startup didn’t want to disclose exact numbers, it says it’s earning in the five-figure range monthly from Amazon’s program.
In addition, Volley is preparing to roll out its own monetization features, including subscriptions and in-app purchases of add-on packs that will extend gameplay.
The company’s games have been well-received for a variety of reasons, but one is that they allow people to play together at the same time — like a modern-day replacement for family game night, perhaps.
“I think a live multiplayer experience with your family or people you’re good friends with, where you can have a fun time together in a room is fairly unusual. I mean, I don’t know about you, but I don’t crowd around my iPhone and play games with my friends. And even with consoles there are significant barriers in understanding how to play,” says Child.
“I think that voice enables the live social experience in a way that anyone from five years old to 85 years old can pick up immediately. I think that’s really special. And I think we’re just at the beginning. I’m not going to say we’ve got it all figured out — but I think that’s powerful and unique to these platforms,” he adds.
Volley raised more than a million in seed funding ahead of joining Y Combinator’s Winter 2018 class, in a round led by Advancit Capital. Other investors include Amplify.LA, Rainfall, Y Combinator, MTGx, NFX and angels Hany Nada, Mika Salmi and Richard Wolpert.
The startup is currently a team of six in San Francisco.
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Here’s why Spotify will go public via direct listing on April 3rd
Spotify explained why it’s ditching the traditional IPO for a direct listing on the NYSE on April 3rd today during its Investor Day presentation. With no lockup period and no intermediary bankers, Spotify thinks it can go public without all the typical shenanigans.
Spotify described the rationale for using a direct listing with five points:
- List Without Selling Shares – Spotify has plent of money with $1.3 billion in cash and securities, has no debt since it converted that into equity for investors, and has positive free cash flow
- Liquidity – Investors and employees can sell on public market and sell at time of their choosing without investors shorting a lockup expiration, while new investors can join in
- Equal Access – Bankers won’t get preferred access. Instead, the whole world will get access at the same time. “No underwriting syndicate, no limited float, no IPO allocations, no preferential treatment”.
- Transparency – Spotify wants to show the facts about its business to everyone via today’s presentation, rather than giving more info to bankers in closed door meetings
- Market-Driven Price Discovery – Rather than setting a specific price with bankers, Spotify will let the public decide what it’s worth. “We think the wisdom of crowds trumps expert intervention”.
Spotify won’t wait for the direct listing, and on March 26th will announce first quarter and 2018 guidance before markets open. It also announced today that there will be no lock-up period, so employees can start selling their shares immediately. This prevents a looming lock-up period expiration that can lead to a dump of shares on the market that sinks the price from spooking investors.
It’s unclear exactly what Spotify will be valued at on April 3rd, but during 2018 its shares have traded on the private markets for between $90 and $132.50, valuing the company at $23.4 billion at the top of the range. The music streaming service now has 159 million monthly active users (up 29 percent in 2017) and 71 million paying subscribers (up 46 percent in 2017.
During CEO Daniel Ek’s presentation, he explained that Spotify emerged as an alternative to piracy by convenience to make paying or ad-supported access easier than stealing. Now he sees the company as the sole leading music streaming service that’s a dedicated music company, subtly throwing shade at Apple, Google, and Amazon. “We’re not focused on selling hardware. We’re not focused on selling books. We’re focused on selling music and connecting artists with fans” said Ek.
Head of R&D Gustav Soderstrom outlined Spotify’s ubiquity strategy, opposed to trying to lock users into a “single platform ecosystem”. He says Spotify does “what’s best for the user and not for the company, and trying to solve the users’ problems by being everywhere.” That’s more shade for Apple, who’s HomePod only works with Apple Music despite customers obviously wishing they could play other streaming services through it.
By now being baked into a wide range of third-party hardware through the Spotify Connect program, Soderstrom says Spotify gets a more holistic understanding of its listeners. He declared that Spotify has 5X as much personalization data as its next closest competitor, and that allows it to know what to play you next. He cheekily calls this “self-driving music”.
Spotify CEO Daniel Ek giving the Investor Day presentation
Directing what people listen to turns Spotify into the new top 40 radio — the hit-maker. That gives it leverage over the record labels so Spotify can get better licensing deals and favorable treatment. Now over 30 percent of Spotify listening is based on its own programming through featured playlists, artists, and more.
There’s plenty of room for Spotify to grow. Only 12 percent of the 1.3 billion payment-enabled smartphones in the world have a streaming music subscription and Spotify makes up half of those. And with the free tier, Spotify has the best way to capture people tip-toeing into streaming.
Wall Street loves a two-sided marketplace, so Spotify is positioning itself in the middle of artists and fans, with each side attracting the other. It’s both selling music streaming services to listeners, and selling the tools to reach and monetize those listeners to musicians. That’s both on its platform, and using its targeting and analytics info to deliver efficient ticket and merchandise promotions elsewhere. Ek discussed the flywheel that drives Spotify’s business, explaining that the more people discover music, the more they listen, and the more artists that become successful on the platform, and the more artists will embrace the platform and bring their fans.
Yet with music catalogues and prices mostly similar across the industry, Spotify will have to depend on its personalized recommendations and platform-agnositic strategy to beat its deep pocketed competitors. Music isn’t going away, so whoever can lock in listeners now at the dawn of streaming could keep coining off them for decades. That’s why Spotify not raising cash for marketing through a traditional IPO is a strange choice. But with its focus on playlists and suggestion data, Spotify could build melodic handcuffs for its listeners who wouldn’t dream of starting from scratch on a competitor.
You can follow along with the presentation here.
For more on Spotify’s not-an-IPO, check out our feature piece:
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The red-hot AI hardware space gets even hotter with $56M for a startup called SambaNova Systems
Another massive financing round for an AI chip company is coming in today, this time for SambaNova Systems — a startup founded by a pair of Stanford professors and a longtime chip company executive — to build out the next generation of hardware to supercharge AI-centric operations.
SambaNova joins an already quite large class of startups looking to attack the problem of making AI operations much more efficient and faster by rethinking the actual substrate where the computations happen. The GPU has become increasingly popular among developers for its ability to handle the kinds of lightweight mathematics in very speedy fashion necessary for AI operations. Startups like SambaNova look to create a new platform from scratch, all the way down to the hardware, that is optimized exactly for those operations. The hope is that by doing that, it will be able to outclass a GPU in terms of speed, power usage, and even potentially the actual size of the chip. SambaNova today said it has raised a huge $56 million series A financing round was co-led by GV and Walden International, with participation from Redline Capital and Atlantic Bridge Ventures.
SambaNova is the product of technology from Kunle Olukotun and Chris Ré, two professors at Stanford, and led by former Oracle SVP of development Rodrigo Liang, who was also a VP at Sun for almost 8 years. When looking at the landscape, the team at SambaNova looked to work their way backwards, first identifying what operations need to happen more efficiently and then figuring out what kind of hardware needs to be in place in order to make that happen. That boils down to a lot of calculations stemming from a field of mathematics called linear algebra done very, very quickly, but it’s something that existing CPUs aren’t exactly tuned to do. And a common criticism from most of the founders in this space is that Nvidia GPUs, while much more powerful than CPUs when it comes to these operations, are still ripe for disruption.
“You’ve got these huge [computational] demands, but you have the slowing down of Moore’s law,” Olukotun said. “The question is, how do you meet these demands while Moore’s law slows. Fundamentally you have to develop computing that’s more efficient. If you look at the current approaches to improve these applications based on multiple big cores or many small, or even FPGA or GPU, we fundamentally don’t think you can get to the efficiencies you need. You need an approach that’s different in the algorithms you use and the underlying hardware that’s also required. You need a combination of the two in order to achieve the performance and flexibility levels you need in order to move forward.”
While a $56 million funding round for a series A might sound colossal, it’s becoming a pretty standard number for startups looking to attack this space, which has an opportunity to beat the big chipmakers and create a new generation of hardware that will be omnipresent among any device that is built around artificial intelligence — whether that’s a chip sitting on an autonomous vehicle doing rapid image processing to potentially even a server within a healthcare organization training models for complex medical problems. Graphcore, another chip startup, got $50 million in funding from Sequoia Capital, while Cerebras Systems also received significant funding from Benchmark Capital.
Olukotun and Liang wouldn’t go into the specifics of the architecture, but they are looking to redo the operational hardware to optimize for the AI-centric frameworks that have become increasingly popular in fields like image and speech recognition. At its core, that involves a lot of rethinking of how interaction with memory occurs and what happens with heat dissipation for the hardware, among other complex problems. Apple, Google with its TPU, and reportedly Amazon have taken an intense interest in this space to design their own hardware that’s optimized for products like Siri or Alexa, which makes sense because dropping that latency to as close to zero as possible with as much accuracy as possible in the end improves the user experience. A great user experience leads to more lock-in for those platforms, and while the larger players may end up making their own hardware, GV’s Dave Munichiello — who is joining the company’s board — says this is basically a validation that everyone else is going to need the technology soon enough.
“Large companies see a need for specialized hardware and infrastructure,” he said. “AI and large-scale data analytics are so essential to providing services the largest companies provide that they’re willing to invest in their own infrastructure, and that tells us more investment is coming. What Amazon and Google and Microsoft and Apple are doing today will be what the rest of the Fortune 100 are investing in in 5 years. I think it just creates a really interesting market and an opportunity to sell a unique product. It just means the market is really large, if you believe in your company’s technical differentiation, you welcome competition.”
There is certainly going to be a lot of competition in this area, and not just from those startups. While SambaNova wants to create a true platform, there are a lot of different interpretations of where it should go — such as whether it should be two separate pieces of hardware that handle either inference or machine training. Intel, too, is betting on an array of products, as well as a technology called Field Programmable Gate Arrays (or FPGA), which would allow for a more modular approach in building hardware specified for AI and are designed to be flexible and change over time. Both Munichiello’s and Olukotun’s arguments are that these require developers who have a special expertise of FPGA, which is a sort of niche-within-a-niche that most organizations will probably not have readily available.
Nvidia has been a major benefactor in the explosion of AI systems, but it clearly exposed a ton of interest in investing in a new breed of silicon. There’s certainly an argument for developer lock-in on Nvidia’s platforms like Cuda. But there are a lot of new frameworks, like TensorFlow, that are creating a layer of abstraction that are increasingly popular with developers. That, too represents an opportunity for both SambaNova and other startups, who can just work to plug into those popular frameworks, Olukotun said. Cerebras Systems CEO Andrew Feldman actually also addressed some of this on stage at the Goldman Sachs Technology and Internet Conference last month.
“Nvidia has spent a long time building an ecosystem around their GPUs, and for the most part, with the combination of TensorFlow, Google has killed most of its value,” Feldman said at the conference. “What TensorFlow does is, it says to researchers and AI professionals, you don’t have to get into the guts of the hardware. You can write at the upper layers and you can write in Python, you can use scripts, you don’t have to worry about what’s happening underneath. Then you can compile it very simply and directly to a CPU, TPU, GPU, to many different hardwares, including ours. If in order to do that work, you have to be the type of engineer that can do hand-tuned assembly or can live deep in the guts of hardware, there will be no adoption… We’ll just take in their TensorFlow, we don’t have to worry about anything else.”
(As an aside, I was once told that Cuda and those other lower-level platforms are really used by AI wonks like Yann LeCun building weird AI stuff in the corners of the Internet.)
There are, also, two big question marks for SambaNova: first, it’s very new, having started in just November while many of these efforts for both startups and larger companies have been years in the making. Munichiello’s answer to this is that the development for those technologies did, indeed, begin a while ago — and that’s not a terrible thing as SambaNova just gets started in the current generation of AI needs. And the second, among some in the valley, is that most of the industry just might not need hardware that’s does these operations in a blazing fast manner. The latter, you might argue, could just be alleviated by the fact that so many of these companies are getting so much funding, with some already reaching close to billion-dollar valuations.
But, in the end, you can now add SambaNova to the list of AI startups that have raised enormous rounds of funding — one that stretches out to include a myriad of companies around the world like Graphcore and Cerebras Systems, as well as a lot of reported activity out of China with companies like Cambricon Technology and Horizon Robotics. This effort does, indeed, require significant investment not only because it’s hardware at its base, but it has to actually convince customers to deploy that hardware and start tapping the platforms it creates, which supporting existing frameworks hopefully alleviates.
“The challenge you see is that the industry, over the last ten years, has underinvested in semiconductor design,” Liang said. “If you look at the innovations at the startup level all the way through big companies, we really haven’t pushed the envelope on semiconductor design. It was very expensive and the returns were not quite as good. Here we are, suddenly you have a need for semiconductor design, and to do low-power design requires a different skillset. If you look at this transition to intelligent software, it’s one of the biggest transitions we’ve seen in this industry in a long time. You’re not accelerating old software, you want to create that platform that’s flexible enough [to optimize these operations] — and you want to think about all the pieces. It’s not just about machine learning.”
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Airtable raises $52M to give non-coders tools to build complex software
A massive company probably has plenty of engineers on staff and the resources to build a complex backbone of interconnected information that can contain tons of data and make acting on it easy — but for smaller companies, and for those that aren’t technical, those tools aren’t very accessible.
That’s what convinced Howie Liu to create Airtable, a startup that looks to turn what seems like just a normal spreadsheet into a robust database tool, hiding the complexity of what’s happening in the background while those without any programming experience create intricate systems to get their work done. Today, they’re trying to take that one step further with a new tool called Blocks, a set of mix-and-match operations like SMS and integrating maps that users can just drop into their systems. Think of it as a way to give a small business owner with a non-technical background to meticulously track all the performance activity across, say, a network of food trucks by just entering a bunch of dollar values and dropping in one of these tools.
“We really want to take this power you have in software creation and ‘consumerize’ that into a form anyone can use,” Liu said. “At the same time, from a business standpoint, we saw this bigger opportunity underneath the low-code app platforms in general. Those platforms solve the needs of heavyweight expensive use cases where you have a budget and have a lot of time. I would position Airtable making a leap toward a graphical user interface, versus a lot of products that are admin driven.”
Liu said the company has raised an additional $52 million in financing in a round led by CRV and Caffeinated Capital, with participation from Freestyle Ventures and Slow Ventures. All this is going toward a way to build a system that is trying to abstract out even the process of programming itself, though there’s always going to be some limited scope as to how custom of a system you can actually make with what amounts to a set of logic operation legos. That being said, the goal here is to boil down all of the most common sets of operations with the long tail left to the average programmers (and larger enterprises often have these kinds of highly-customized needs).
All this is coming at a time when businesses are increasingly chasing the long tail of small- to medium-sized businesses, the ones that aren’t really on the grid but represent a massive market opportunity. Those businesses also probably don’t have the kinds of resources to hire engineers while companies like Google or Facebook are camping out on college campuses looking to snap up students graduating with technical majors. That’s part of the reason why Excel had become so popular trying to abstract out a lot of complex operations necessary to run a business, but at the same time, Liu said that kind of philosophy should be able to be taken a step further.
“If you look at cloud, you have Amazon’s [cloud infrastructure] EC2, which abstracted the hardware level and you can build on existing machine intelligence,” Liu said. “Then, you get the OS level and up. Containers, Heroku, and other tools have extracted away the operation level complexity. But you have to write the app and modal logic. Our goal is to go a big leap forward on top of that and abstract out the app code layer. You should be able to directly use our interface, and blocks, all these plug and play lego pieces that give you more dynamic functionality — whether a map view or an integration with Twilio.”
And, really, all these platforms like Twilio have tried to make themselves pretty friendly to coding beginners as-is. Twilio has a lot of really good documentation for first-time developers to learn to use their platforms. But Airtable hopes to serve as a way to interconnect all these things in a complex web, creating a relational database behind the scenes that users can operate on in a more simplistic matter that’s still accurate, fast, and reliable.
“Obviously MySQL is great if you want to use code or custom SQL queries to interface with the data,” Liu said. “But, ultimately, you’d never as a business end user consider using literally a terminal-based SQL prompt as the primary interface to and from your data. Certainly you wouldn’t put that on your designs. Clearly you would want some interface on top of the SQL level database. We basically expose the full value of a relational database like Postgres to the end user, but we also give them something equally but more important: the interface on the top that makes the data immediately visible.”
There’s been a lot of activity trying to rethink these sort of fundamental formats that the average user is used to, but are ripe for more flexibility. Coda, a startup trying to rethink the notion behind a word document, raised $60 million, and all this points towards moves to try to create a more robust toolkit for non-technical users. That also means that it’s going to be an increasingly hot space, and especially look like an opportunity for companies that are already looking to host these kinds of services online like Amazon or Microsoft and have the buy-in from those businesses.
Liu, too, said that the goal of the company was to go after all potential business cases right away by creating a what-you-see-is-what-you-get one size fits all platform — which is usually called a horizontal approach. That’s often a very risky move, and it’s probably the biggest question mark for the company as there’s an opportunity for some other startups or companies to come in and grab niches of that whole pie in specific areas (like, say, a custom GUI programming interface for healthcare). But Liu said the opportunity for Airtable was to go horizontal from day one.
“There’s this assumption that software has to involve literally writing code,” Liu said. “It’s sort of a difficult thing to extricate ourselves from because we have built so much with writing code. But when you think about what goes into a useful application, especially in the business-to-business internal tools in a company use case which forms the bulk of software that’s consumed in terms of lines of code written, most of them are primarily a relational database model, and the relational database aspect of it is not an arbitrary format.
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TypingDNA launches Chrome extension that verifies your identity based on typing
TypingDNA has a new approach to verifying your identity based on how you type.
The startup, which is part of the current class at Techstars NYC, is pitching this as an alternative to two-factor authentication — namely, the security feature that sends unique codes to a separate device (usually your phone) to make sure someone else isn’t logging in with your password.
The problem with two factor? TypingDNA Raul Popa put it simply: “It’s a bad user experience … Nobody wants to use a different device.” (I know that TechCrunch writers have had two-factor issues of their own, like when they’re trying to log in on an airplane and can’t connect their phone.)
So TypingDNA allows users to verify their identity without having to whip out their phone. Instead, they just enter their name and password into a window, then TypingDNA will analyze their typing and confirm that it’s really them.
The startup’s business model revolves around working with partners to incorporate the technology, but it’s also launching a free Chrome extension that works as an alternative to two-factor authentication on a wide range of services, including Amazon Web Services, Coinbase and Gmail.
Popa said TypingDNA measures two key aspects of your typing: How long it takes you to reach a key and how long you keep the key pressed down. Apparently these patterns are unique; Popa showed me that the system could tell the difference between his typing and mine, and you can test it out for yourself on the TypingDNA website.
He also said that the company can adjust the strictness of the system, getting the rate of false positives as low as 0.1 percent. In the case of the Chrome authenticator, Popa said, “We minimize the false acceptance rate” — so you might get rejected if you’re typing in an unusual position, or if there’s some other reason you’re typing slower or faster than usual. But in that case, the authenticator will just ask you to try again.
And again, you can use the Chrome extension on a variety of sites. Most two-factor options include confirming a device using a QR code, which TypingDNA can grab. The two-factor codes are then sent to the TypingDNA extension (the codes are stored locally on your computer, not the company’s servers), and they’re revealed once you’ve verified your identity with the aforementioned typing.
You can visit TypingDNA to learn more and download the extension.
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Spotify tests native voice search, groundwork for smart speakers
Now Spotify listens to you instead of the other way around. Spotify has a new voice search interface that lets you say “Play my Discover Weekly,” “Show Calvin Harris” or “Play some upbeat pop” to pull up music.
A Spotify spokesperson confirmed to TechCrunch that this is “Just a test for now,” as only a small subset of users have access currently, but the company noted there would be more details to share later. The test was first spotted by Hunter Owens. Thanks to him we have a video demo of the feature below that shows pretty solid speech recognition and the ability to access music several different ways.
Voice control could make Spotify easier to use while on the go using microphone headphones or in the house if you’re not holding your phone. It might also help users paralyzed by the infinite choices posed by the Spotify search box by letting them simply call out a genre or some other category of songs. Spotify briefly tested but never rolled out a very rough design of “driving mode” controls a year ago.
Down the line, Spotify could perhaps develop its own voice interface for smart speakers from other companies or that it potentially builds itself. That would relieve it from depending on Apple’s Siri for HomePod, Google’s Assistant for Home or Amazon’s Alexa for Echo — all of which have accompanying music streaming services that compete with Spotify. Apple chose to make its HomePod speaker Apple Music-only, cutting out Spotify. Its Siri service similarly won’t let people make commands inside third-party apps, so you can ask your iPhone to play a certain song on Apple Music, but not Spotify.
To date, Spotify has only worked with manufacturers to build its Spotify Connect features into boomboxes and home stereos from companies like Bose, rather than creating its own hardware. If it chooses to make Spotify-branded speakers, it might need some of its own voice technology to power them.
Spotify is preparing for a direct listing that will make the company public without a traditional IPO. That means forgoing some of the marketing circus that usually surrounds a company’s debut. That means Spotify may be even more eager to experiment with features or strategies that could be future money-makers so that public investors see growth potential. Breaking into voice directly instead of via its competitors could provide that ‘x-factor.’
For more on Spotify’s not-an-IPO, check out our feature story:
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PlayTable uses blockchain to connect video games and physical objects
I’ll be honest: When I first got the pitch for “the first blockchain-based video game console,” I assumed it must be some kind of gimmick.
But Jimmy Chen, co-founder and CEO of Blok.Party, said the Ethereum blockchain is “a critical part of this experience,” allowing his team to create “this seamless bridge between the digital and physical worlds.”
Today, Blok.Party is unveiling its PlayTable console, which combines elements of tabletop and console gaming.
This isn’t the first time someone’s tried to incorporate real-world objects into video games — for example, there was Disney Infinity, which shut down a couple of years ago. But by using blockchain technology, Chen said he can avoid many of the pitfalls that tripped up previous efforts.
For one thing, instead of manufacturing new toys and pieces for every game, PlayTable uses RFID tags, which can be attached to existing objects. So players can use the tags to incorporate their own toys and cards into the games.
“We’ve been trying to make toys smart for a very, very long time, but all we’ve been doing is stuffing resistors and transistors inside of them, making them incresingly more inaccessible,” Chen said. Blok.Party, in contrast, is “creating a data set that is inexpensive, that can easily attach to the physical object.”
He demonstrated PlayTable for me using Battlegrid, a card-based fantasy duel game developed by Blok.Party, which Chen described as “if Magic the Gathering, Hearthstone and Skylanders had a baby.” I won’t pretend that I followed all the ins and outs of the battle, but I saw that Chen could place different cards and pieces down and the table would recognize them and bring the related characters into play.
“The core of it, the physical manifestation of it that exists only in one space, has proven to be fairly difficult [in the past],” Chen added. “By creating that backend infrastructure, we can make the system a lot more successful. The element that blockchain really enables is this idea of having a truly unique, open dataset that people can contribute to and can build on top of.”
Chen said Blok.Party is working with third-party developers to create about 25 different titles, some of them based on classic games like poker and mah jong.
The PlayTable is currently available for pre-order at a discounted price of $349. (The company says the regular price will be $599.) The plan is to ship the console in the fourth quarter of this year.
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Pilot raises $15M to bring bookkeeping into the modern era
The first time Waseem Daher, Jessica McKellar, and Jeff Arnold worked together on a startup, they built one that allowed administrators to patch security updates to a system without having to restart it.
So it might come as a bit of a surprise that the next big technical challenge the three MIT graduates want to tackle is bookkeeping . But after selling Ksplice to Oracle back in 2011, it was actually the financial software they had built internally that made the jaws of the finance teams at Oracle drop, Daher said. They had created a continuously-updating internal version of QuickBooks, keeping a close eye on their spending and accounting and not having do hire a bookkeeper to do so, out of pure frustration with the process. And today that’s basically launching as Pilot, a startup that has now raised $15 million in a financing round led by Index Ventures.
“If you look at the history of bookkeeping, it goes back to the 1400s,” Daher said. “Probably the oldest written records were of transactions. Around 1400s, we invented double-entry bookkeeping, a system for how money moves into and out of various accounts of companies. That system, as articulated in 1400 in Venice, is basically still what people do in every American business today. You hire a bookkeeper or bookkeeping firm, you send them all your stuff and they track and produce the set of books. The way it’s done today is the same way it’s done in the 90s, the 40s.”
When a company starts working with Pilot, the actual core experience on the customer side doesn’t really change all that much: they still work with a human on the other end. But the bookkeeper from Pilot is working with the internal tools they have built to bring in the data from the company, organize it and structure it, and produce a set of books that are more accurate than someone might have produced than just doing it by hand. Customers will get the kinds of questions you might expect from a normal bookkeeper as they look to clarify what’s happening, but in the end the process happens much more seamlessly. They can integrate directly with their existing services like Expensify or Gusto (or ask Pilot to help out with that) and then go from there.
That kind of human-software mix is something that’s increasingly common in services businesses — like Pilot — as the tech industry figures out what should be automated and what should still be handled by a person. There are still a lot of things that a person can catch, but there’s also the actual human relationship, which isn’t a kind of repetitive task you’d want to automate with an algorithm. To begin, Pilot isn’t trying to force companies to completely rip out their bookkeeping software and start from scratch, and instead start to collect the electronic information they already have.
“Uber’s like that, the drivers are humans but the software makes them much more effective,” Index Ventures’ Mike Volpi said. “You can see it in a lot of applications where in IT support there’s a few businesses like this, you troubleshoot using software, and when you can’t you fix it pass it to humans. In customer service chats, a lot of times it’s an AI, and when the questions get tricky enough it rolls over to humans. It’s interesting because there are tasks which humans are fundamentally needed and there are tasks that are mundane that software can do and the human can avoid doing. It’s an interesting thesis around this hybrid.”
Prior to Pilot, the team sold another company to Dropbox called Zulip, and spent some time at the company as it continued to scale up (Dropbox is now in the process of going public). Some of the challenge alone was somehow assembling a team that found some fascination with the intersection of accounting, machine learning and working directly with customers, but so far McKellar said that they’ve been able to put one together thus far. And, more importantly, now that they are starting to roll out their service they can start getting some perspective on the industry as a whole.
“I think people can get motivated by almost any problem if you know you’re tackling a big problem for many people,” McKellar said. “But there’s quite a lot of subtlety to what we’re building. The rules and principles of bookkeeping are well define but the real world is really messy, and designing the right systems to automate bookkeeping at scale is actually a tricky thing. We have an incredible engineering team that is able to tackle this with the right mindset it. The analogy you can draw is self-driving cars — that’s a system normally done by a human, everyone understands what it takes to drive a car, what actions you should take. It’s difficult for people to put into words, what are the rules given a set of inputs, but it needs to work and be reliable.”
As more and more of this information comes in, and more and more companies start to work with Pilot, they can start spotting trends in the industry. For example, if a 17th SaaS business with a similar business model to other Pilot companies signs up, they could down the line take a look at their info and spot potential discrepancies based on anonymized trend data picked up from other comparables in the industry — or do a better job of spotting inefficiencies or others. And there are some obvious funnels for this already, like getting the right information for tax purposes to accountants.
There’s going to be a lot of increasing activity in this space, though. Already you’re seeing some funded projects like botkeeper, which are looking to find some ways to automate a bookkeeping service. There’s nothing quite so formalized and an obvious tool that looks to take out QuickBooks (and, again, a lot of these seem to be playing nice for now), and there’s always the chance that Intuit could try to take on the space itself. But at the end of the day, Volpi says it’s based on the team that they’ve assembled — and that combination of humans and algorithms — that gives them a shot at succeeding.
“If you look at a fundamental level, the bookkeeping for the doctor’s office or florist, it is really all following the same underlying principles,” McKellar said. “One of the engineering challenges is to build the tooling and systems and software in a way that’s intelligent. It has to be a set of processes that can flexibly accommodate every vertical over time. In some sense this company, why we raised this, was to validate a huge hypothesis — it’s possible to automate bookkeeping at scale across a range of industries.”
Here’s the rest of the investors in this round, since it’s a long list: Patrick and John Collison, Drew Houston, Diane Greene, Frederic Kerrest, Hans Robertson, Adam D’Angelo, Paul English, Howard Lerman, Joshua Reeves, Tien Tzuo, as well as many others.
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